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Sentiment analysis usually refers to the analysis of human-generated content via a polarity filter. Affective computing deals with the exact emotions conveyed through information. Emotional information most frequently cannot be accurately described by a single emotion class. Multilabel classifiers can categorize human-generated content in multiple emotional classes. Ensemble learning can improve the statistical, computational and representation aspects of such classifiers. We present a baseline stacked ensemble and propose a weighted ensemble. Our proposed weighted ensemble can use multiple classifiers to improve classification results without hyperparameter tuning or data overfitting. We evaluate our ensemble models with two datasets. The first dataset is from Semeval2018-Task 1 and contains almost 7000 Tweets, labeled with 11 sentiment classes. The second dataset is the Toxic Comment Dataset with more than 150,000 comments, labeled with six different levels of abuse or harassment. Our results suggest that ensemble learning improves classification results by 1.5 % to 5.4 % .

Operating centrifugal pumps under two-phase flow conditions presents challenges such as phase separation, cavitation, and flow instabilities, compromising reliability and performance. A specialized design is crucial to mitigate these issues. This study utilized computational fluid dynamics (CFDs) to understand two-phase flow behavior and assess the impact of different blade geometries on pump performance under such conditions. For this purpose, the inhomogeneous multiphase model was employed, wherein the momentum and continuity flow equations were individually solved for each phase across three different impellers with varying blade angle distributions. The computational results indicated higher gas concentrations on the pressure side of the blade, with gas pocket size correlating with flow rate and inlet gas concentration. The blade angle distribution’s effect was more pronounced with increased gas concentrations, while a tendency of gas bubbles to coalesce towards the impeller shroud was also observed. The presence of gas promoted flow recirculation and separation, substantially reducing impeller performance. Blade angle distribution critically influenced the flow field, affecting flow separation, stability, efficiency, and overall performance, highlighting the importance of optimized blade design for enhanced centrifugal pump performance in liquid–gas two-phase flow conditions.

Nowadays, social networks incessantly influence the lives of young people. Apart from entertainment and informational purposes, social networks have penetrated many fields of educational practices and processes. This review tries to highlight the use of social networks in higher education, as well as points out some factors involved. Moreover, through a literature review of related articles, we aim at providing insights into social network influences with regard to (a) the learning processes (support, educational processes, communication and collaboration enhancement, academic performance) from the side of students and educators; (b) the users’ personality profile and learning style; (c) the social networks as online learning platforms (LMS—learning management system); and (d) their use in higher education. The conclusions reveal positive impacts in all of the above dimensions, thus indicating that the wider future use of online social networks (OSNs) in higher education is quite promising. However, teachers and higher education institutions have not yet been highly activated towards faster online social networks’ (OSN) exploitation in their activities.

The Epstein–Barr virus (EBV) is linked to various B-cell lymphomas, including Burkitt lymphoma (BL), classical Hodgkin lymphoma (cHL) and diffuse large B-cell lymphoma (DLBCL) at frequencies ranging, by routine techniques, from 5 to 10% of cases in DLBCL to >95% in endemic BL. Using higher-sensitivity methods, we recently detected EBV traces in a few EBV-negative BL cases, possibly suggesting a “hit-and-run” mechanism. Here, we used routine and higher-sensitivity methods (qPCR and ddPCR for conserved EBV genomic regions and miRNAs on microdissected tumor cells; EBNA1 mRNA In situ detection by RNAscope) to assess EBV infection in a larger lymphoma cohort [19 BL, 34 DLBCL, 44 cHL, 50 follicular lymphomas (FL), 10 T-lymphoblastic lymphomas (T-LL), 20 hairy cell leukemias (HCL), 10 mantle cell lymphomas (MCL)], as well as in several lymphoma cell lines (9 cHL and 6 BL). qPCR, ddPCR, and RNAscope consistently documented the presence of multiple EBV nucleic acids in rare tumor cells of several cases EBV-negative by conventional methods that all belonged to lymphoma entities clearly related to EBV (BL, 6/9 cases; cHL, 16/32 cases; DLBCL, 11/30 cases), in contrast to fewer cases (3/47 cases) of FL (where the role of EBV is more elusive) and no cases (0/40) of control lymphomas unrelated to EBV (HCL, T-LL, MCL). Similarly, we revealed traces of EBV infection in 4/5 BL and 6/7 HL cell lines otherwise conventionally classified as EBV negative. Interestingly, additional EBV-positive cases (1 DLBCL, 2 cHL) relapsed as EBV-negative by routine methods while showing EBNA1 expression in rare tumor cells by RNAscope. The relapse specimens were clonally identical to their onset biopsies, indicating that the lymphoma clone can largely loose the EBV genome over time but traces of EBV infection are still detectable by high-sensitivity methods. We suggest EBV may contribute to lymphoma pathogenesis more widely than currently acknowledged.

Burkitt lymphoma (BL) is an aggressive mature B-cell lymphoma that represents one of the most studied human malignancies. Initially described in equatorial Africa by the Irish surgeon Denis P. Burkitt, African (endemic) Burkitt lymphoma was the first human neoplasm shown to be associated with a virus, the Epstein–Barr virus (EBV), and also the first human neoplasm shown to harbor a recurrent chromosomal aberration, the t(8;14) (q24;q32) translocation that led to the identification of the central role of the MYC gene in tumorigenesis. In this review, we provide a brief historical introduction, followed by a presentation of important aspects of epidemiology, pathogenesis, and of diagnostic features including morphology, cytogenetics and molecular findings. We also provide a comprehensive overview of the findings convincingly demonstrating that subtyping of BL into EBV-positive and EBV-negative better describes the biological heterogeneity of this lymphoma entity than the historical subtyping into endemic, sporadic, and immunodeficiency-associated. As the distinction of BL from other B-cell lymphomas is important for providing optimal oncological care, we also discuss the differential diagnosis and how this lymphoma can be distinguished from other aggressive B-cell lymphomas.

The rise of Online Social Networks has reshaped global discourse, enabling real-time conversations on complex issues such as irregular migration. Yet the informal, multilingual, and often noisy nature of content on platforms like X (formerly Twitter) and Telegram presents significant challenges for reliable automated analysis. This study presents an exploratory multilingual natural language processing (NLP) framework for detecting irregular migration discourse across five languages. Conceived as a pilot study addressing extreme data scarcity in sensitive migration contexts, this work evaluates transformer-based models on a curated multilingual corpus. It provides an initial baseline for monitoring informal migration narratives on X and Telegram. We evaluate a broad range of approaches, including traditional machine learning classifiers, SetFit sentence-embedding models, fine-tuned multilingual BERT (mBERT) transformers, and a Large Language Model (GPT-4o). The results show that GPT-4o achieves the highest performance overall (F1-score: 0.84), with scores reaching 0.89 in French and 0.88 in Greek. While mBERT excels in English, SetFit outperforms mBERT in low-resource settings, specifically in Arabic (0.79 vs. 0.70) and Greek (0.88 vs. 0.81). The findings highlight the effectiveness of transformer-based and large-language-model approaches, particularly in low-resource or linguistically heterogeneous environments. Overall, the proposed framework provides an initial, compact benchmark for multilingual detection of irregular migration discourse under extreme, low-resource conditions. The results should be viewed as exploratory indicators of model behavior on this synthetic, small-scale corpus, not as statistically generalizable evidence or deployment-ready tools. In this context, “multilingual” refers to robustness across different linguistic realizations of identical migration narratives under translation, rather than coverage of organically diverse multilingual public discourse.

Short-form video platforms such as TikTok (TikTok Pte. Ltd., Singapore) host large volumes of user-generated, often ephemeral, content related to irregular migration, where relevant cues are distributed across visual scenes, on-screen text, and multilingual captions. Automatically identifying migration-related videos is challenging due to this multimodal complexity and the scarcity of labeled data in sensitive domains. This paper presents an interpretable multimodal classification framework designed for deployment under data-scarce conditions. We extract features from platform metadata, automated video analysis (Google Cloud Video Intelligence), and Optical Character Recognition (OCR) text, and compare text-only, OCR-only, and vision-only baselines against a multimodal fusion approach using Logistic Regression, Random Forest, and XGBoost. In this pilot study, multimodal fusion consistently improves class separation over single-modality models, achieving an F1-score of 0.92 for the migration-related class under stratified cross-validation. Given the limited sample size, these results are interpreted as evidence of feature separability rather than definitive generalization. Feature importance and SHAP analyses identify OCR-derived keywords, maritime cues, and regional indicators as the most influential predictors. To assess robustness under data scarcity, we apply SMOTE to synthetically expand the training set to 500 samples and evaluate performance on a small held-out set of real videos, observing stable results that further support feature-level robustness. Finally, we demonstrate scalability by constructing a weakly labeled corpus of 600 videos using the identified multimodal cues, highlighting the suitability of the proposed feature set for weakly supervised monitoring at scale. Overall, this work serves as a methodological blueprint for building interpretable multimodal monitoring pipelines in sensitive, low-resource settings.

The prospective multicentre Phase II PTLD-2 trial (NCT02042391) tested modified risk-stratification in adult SOT recipients with CD20-positive PTLD based on principles established in the PTLD-1 trials: sequential treatment and risk-stratification. After rituximab monotherapy induction, patients in complete remission as well as those in partial remission with IPI < 3 at diagnosis (low-risk) continued with rituximab monotherapy and thus chemotherapy free. Most others (high-risk) received R-CHOP-21. Thoracic SOT recipients who progressed (very-high-risk) received alternating R-CHOP-21 and modified R-DHAOx. The primary endpoint was event-free survival (EFS) in the low-risk group. The PTLD-1 trials provided historical controls. Rituximab was applied subcutaneously. Of 60 patients enrolled, 21 were low-risk, 28 high-risk and 9 very-high-risk. Overall response was 45/48 (94%, 95% CI 83–98). 2-year Kaplan–Meier estimates of time to progression and overall survival were 78% (95% CI 65–90) and 68% (95% CI 55–80) – similar to the PTLD-1 trials. Treatment-related mortality was 4/59 (7%, 95% CI 2–17). In the low-risk group, 2-year EFS was 66% (95% CI 45–86) versus 52% in the historical comparator that received CHOP (p = 0.432). 2-year OS in the low-risk group was 100%. Results with R-CHOP-21 in high-risk patients confirmed previous results. Immunochemotherapy intensification in very-high-risk patients was disappointing.

Background A persistent distal false lumen after surgery for DeBakey type I acute aortic dissection (AAD) is associated with increased risk of adverse aortic events (AAEs). This pilot randomized controlled trial aimed to evaluate whether elective thoracic endovascular aortic repair (TEVAR), performed 1–3 months after type I AAD surgery in selected high-risk patients, promotes aortic remodeling and improves clinical outcomes. Methods Thirty-two patients who underwent surgical repair for type I AAD were randomized to either elective TEVAR ( n  = 15) or standard conservative management ( n  = 17). CT angiography–based inclusion criteria were: (a) a re-entry tear in Ishimaru zones 3 or 4, and (b) a maximum descending thoracic aorta (DTA) diameter > 40 mm and/or a false lumen diameter > 20 mm. One-year follow-up included clinical assessment and CT angiography. Results The TEVAR group exhibited significantly more favorable aortic remodeling than the conservative group, as demonstrated by greater reductions in total aortic diameter (zones 2–9), greater increases in true lumen diameter (zones 3–8), and greater reductions in false lumen diameter (zones 2–8). Complete false lumen thrombosis was also more frequent in the TEVAR group (zones 2–6). Clinically, the TEVAR group had significantly lower rates of dissection extension (0% vs. 29.4%; p  = 0.050), rehospitalization due to complications (0% vs. 58.8%; p  < 0.001), and long-term AAEs (20.0% vs. 58.8%; p  = 0.026). Conclusions In selected high-risk patients, performing TEVAR 1–3 months after surgical repair of type I AAD may promote favorable aortic remodeling and be associated with improved one-year clinical outcomes. Clinical registration number This study is registered with ISRCTN under the title “Endovascular Repair After Aortic Dissection Type I or Conservative – Aortic Remodeling Enhancement (ERADICARE Trial),” registration number ISRCTN 11,964,494 ( https://doi.org/10.1186/ISRCTN11964494 ).

Post-transplantation lymphoproliferative disorder (PTLD) develops in 1–10% of transplant recipients and can be Epstein–Barr virus (EBV) associated. To improve long-term efficacy after rituximab monotherapy and to avoid the toxic effects of CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisolone) chemotherapy seen in first-line treatment, we initiated a phase 2 trial to test whether the subsequent use of rituximab and CHOP would improve the outcome of patients with PTLD. In this international multicentre open-label phase 2 trial, treatment-naive adult solid-organ transplant recipients diagnosed with CD20-positive PTLD who had failed to respond to upfront immunosuppression reduction received four courses of rituximab (375 mg/m2 intravenously) once a week followed by 4 weeks without treatment and four cycles of CHOP every 3 weeks. In case of disease progression during rituximab monotherapy, CHOP was started immediately. Supportive therapy with granulocyte-colony stimulating factor after chemotherapy was mandatory and antibiotic prophylaxis was recommended. The primary endpoint was treatment efficacy measured as response rates in all patients who completed treatment with rituximab and CHOP, per protocol, and response duration, in all patients who completed all planned therapy and responded. Secondary endpoints were frequency of infections, treatment-related mortality, and overall survival. This study is registered at ClinicalTrials.gov, number NCT01458548. 74 patients were enrolled between Dec 12, 2002 and May 5, 2008, of whom 70 patients were eligible to receive treatment. PTLD was of late type in 53 (76%) of 70 patients, monomorphic in 67 (96%) of 70, and histologically EBV associated in 29 (44%) of 66 cases. Four of 70 patients did not receive CHOP. 53 of 59 patients had a complete or partial response (90%, 95% CI 79–96), of which 40 (68%, 55–78) were complete responses. At data cutoff (June 1, 2011) median response duration in the 53 patients who had responded to treatment had not yet been reached (>79·1 months). The main adverse events were grade 3–4 leucopenia in 42 of 62 patients (68%, 55–78) and infections of grade 3–4 in 26 of 64 patients (41%, 29–53). Seven of 66 patients (11%, 5–21) had CHOP-associated treatment-related mortality. Median overall survival was 6·6 years (95% CI 2·8–10·4; n=70). Our results support the use of sequential immunochemotherapy with rituximab and CHOP in PTLD. F Hoffmann-La Roche, Amgen Germany, Chugaï France.